A modular tool to aggregate results from bioinformatics analyses across many samples into a single report.
This report has been generated by the PavlidisLab/sc-annotation-pipeline analysis pipeline.
/space/grp/rschwartz/rschwartz/cell_annotation_cortex.nf/work/68/207d7032a592150946d5edf4bf1111/GSE180670
Sample Outlier Composition (outliers)
Composition per sample of predicted outliers: outlier_mito = mitochondrial outliers; outlier_ribo = ribosomal outliers; outlier_hb = hemoglobin outliers; counts_outlier = outlier of log1p_n_genes ~ log1p_n_counts; predicted_doublet = doublets predicted by sc.pp.scrublet;.
Sample cell type composition
Composition per sample of predicted cell types.
Leiden Cluster Composition (outliers)
Leiden clustering performed on log-transformed data with top 2000 variable genes, 10 PCs, 30 neighbors, resolution = 0.3.
Leiden cluster composition (cell types)
Leiden clustering performed on log-transformed data with top 2000 variable genes, 10 PCs, 30 neighbors, resolution = 0.3.
Cell type outlier composition
Cell type markers
Expression of select markers. Count are averaged across cell-type labels and z-score normalized across genes.
Cell type UMAP
UMAP of the cell type labels, sample names and leiden clusters.